Comparative linguistic analysis of noun affixal derivatives
PDF
DOI

Keywords

predicative expression, nouns

How to Cite

Comparative linguistic analysis of noun affixal derivatives. (2023). Journal of Universal Science Research, 1(4), 308-311. https://universalpublishings.com/~niverta1/index.php/jusr/article/view/483

Abstract

The verb-noun pairings in the Princeton WordNet were subjected to a morphosemantic analysis. The findings are shown in the standoff file, which has pairs annotated with a set of 14 semantic connections. We detected the affixes, automatically differentiated between zero-derivation and affixal derivation in the data, and manually verified the outcomes. The findings indicate that an affix predominates in the creation of new words for each semantic relation. However we are unable to discuss their specificity with regard to such a relation. Additionally, for each semantic connection, some verb-noun semantic prime pairings are better represented than others, leading to the emergence of various semantic clusters (in the form of WordNet subtrees). In order to capture finer regularities in the derivation process as represented in the semantic properties of the words involved and as reflected in the structure of the lexicon, we therefore employ a large-scale data-driven linguistically motivated analysis made possible by the rich derivational and morphosemantic description in WordNet. [1:42]

PDF
DOI

References

L. Bauer, R. Lieber, I. Plag. 2013. The Oxford Reference Guide to English Morphology. Oxford University Press.

B. Cetnarowska. 1993. The Syntax, Semantics and Derivation of Bare Nominalisations in English. Katowice. Uniwersytet Slaski.

E. Clark, and H. H. Clark. 1979. When Nouns Surface as Verbs. Language. 55 (4).

Ch. Fellbaum (ed.). 1998. WordNet: An Electronic Lexical Database. Cambridge, MA: MIT Press.

Ch. Fellbaum, A. Osherson, and P. E. Clark. 2009. Putting Semantics into WordNet’s ‘Morphosemantic’ Links. In: Z. Vetulani, H. Uszkoreit (eds) Human Language Technology. Challenges of the Information Society. LTC 2007. Lecture Notes in Computer Science, vol 5603. Springer, Berlin, Heidelberg.

S. Koeva, S. Leseva, I. Stoyanova, T. Dimitrova, M. Todorova. Automatic Prediction of Morphosemantic Relations. In: Proceedings of GWC 2016. Bucharest. R. Lieber. 2004. Morphology and Lexical Semantics. Cambridge University Press.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.